TL;DR in plain English
- Keenable offers a web-search API you can call from an agent or service to fetch live web passages for grounding answers. See https://keenable.ai/.
- Key public snapshot facts: 100B+ documents indexed, US‑East p95 latency reported under 250 ms, and published pricing shown from about $1 per 1,000 requests at high throughput (100 RPS+) (https://keenable.ai/).
- Fast, lower-cost search lets your assistant perform more lookups with less delay and lower monthly bills compared to expensive alternatives.
Quick immediate steps (5–30 minutes):
- Create a Console account at https://keenable.ai/ and copy an API key.
- Run a short set of representative queries and measure latency and relevance.
- If acceptable, wire a single HTTP call into your retrieval step.
Short validation checklist:
- [ ] Acquire API key from the Keenable Console (https://keenable.ai/)
- [ ] Run a small set of test queries and inspect responses
- [ ] Confirm p95 and cost numbers in your Console region (https://keenable.ai/)
Methodology note: this guide cites the public Keenable snapshot at https://keenable.ai/ for index size, latency, and pricing.
What you will build and why it helps
Concrete goal: add one retrieval step that calls Keenable, extracts the top passages, deduplicates by URL, and returns a compact JSON payload your LLM can consume. See https://keenable.ai/.
Why this is useful (public snapshot facts):
- Index scale: 100B+ documents (https://keenable.ai/).
- Latency: US‑East p95 reported under 250 ms (https://keenable.ai/).
- Pricing: published pricing shown from about $1 per 1,000 requests at 100 RPS+ (https://keenable.ai/).
- Benchmarking: the site reports 7‑day mean performance on NEEDLE and shows result-quality bands (example bands: 80%, 70%, 60%, 50%) (https://keenable.ai/).
High-level retrieval mapping (example):
| Query intent | Retrieval strategy | Result window (examples) | |---|---:|---:| | Short factual check | Top 1–3 passages, strict dedupe | 1–3 | | Extract structured fields | Top 3–5 passages, parse URLs with clear snippets | 3–5 | | Broad research | Expand to more passages or combine providers | 10–20 |
Concrete numbers you can rely on from the public snapshot: 100B+ documents; US‑East p95 <250 ms; pricing near $1 per 1,000 requests at high throughput (100 RPS+) (https://keenable.ai/).
Before you start (time, cost, prerequisites)
Time estimates (rough):
- Smoke test: 30–60 minutes to sign up and run initial queries (https://keenable.ai/).
- Minimal integration: ~2 hours to add a single HTTPS call and parse results.
- Production hardening: 1–2 days to add caching, monitoring, and rollout controls.
Cost signals from the public page: pricing is shown from about $1 per 1,000 requests at the 100 RPS+ tier; verify exact billing and regional pricing in your Console (https://keenable.ai/).
Minimal prerequisites:
- An environment that can make HTTPS requests and store a secret API key.
- Basic logging and metrics to capture latency percentiles and sample responses.
- Access to the Keenable Console to check endpoints, quotas, and docs (https://keenable.ai/).
Preflight checklist:
- [ ] API key stored in a secrets vault
- [ ] Confirm region and Console-reported p95 (prefer US East if you need lower latency) (https://keenable.ai/)
- [ ] Confirm billing plan and quotas in Console
Step-by-step setup and implementation
All endpoint names and exact JSON fields should be verified in the Keenable Console and docs: https://keenable.ai/.
- Sign up and get a key
- Create a Console account at https://keenable.ai/ and copy the API key.
- Smoke test (small set of queries)
- Run ~10 focused queries. Measure p50 and p95 latency and inspect result snippets for relevance.
Example curl command (replace placeholders):
export KEENABLE_KEY="sk-..."
export KEENABLE_ENDPOINT="https://api.keenable.example/search"
curl -s -H "Authorization: Bearer $KEENABLE_KEY" \
-H "Content-Type: application/json" \
-d '{"query":"latest electric vehicle battery lifespan 2024"}' \
"$KEENABLE_ENDPOINT"
- Minimal integration
- Make a synchronous HTTPS request with Authorization. Parse top N results and extract snippet + URL + metadata. Return a compact JSON that your LLM can read.
Example configuration (YAML):
keenable:
endpoint: "https://api.keenable.example/search"
api_key: "${KEENABLE_KEY}"
timeout_ms: 1500
max_retries: 3
max_top_results: 5
- Monitoring and fallback
- Emit latency percentiles and success rates from your client. On errors, return a cached result or a safe default.
Plain-language flow summary: call Keenable, take top N snippets, dedupe by URL, and hand the LLM a short JSON context. This keeps latency predictable and limits per-user billing.
Notes and links: confirm exact JSON fields, SDKs, and endpoints in the Keenable Console (https://keenable.ai/).
Common problems and quick fixes
Start troubleshooting by checking the Keenable Console and docs: https://keenable.ai/.
| Symptom | Likely cause | Quick fix | |---|---|---| | High p95 | Network region mismatch or client timeout | Test from preferred region; increase client timeout | | Unexpected cost | Missing caching or background jobs issuing queries | Add caching, throttle batch jobs | | 429 rate-limits | Too many RPS or quota exceeded | Implement exponential backoff; request quota increase in Console | | Low recall for niche topics | Coverage gap | Increase result window or add a secondary provider |
Quick troubleshooting checklist:
- [ ] Verify API key and active plan in Console (https://keenable.ai/)
- [ ] Confirm region and measured p95 from your client
- [ ] Inspect sample responses for format and coverage issues
First use case for a small team
Scenario: a 2–4 person startup building a customer-support assistant grounded in live web sources via Keenable (https://keenable.ai/).
Suggested timeline and gates:
- Hour 0–4: Console experiments and 10–20 focused queries to inspect relevance and latency.
- Day 1: Integrate a single retrieval call into the assistant and log responses.
- Day 2–7: Add simple caching, collect metrics, and run a small canary.
Operational checklist for a small team:
- [ ] API key and rotation schedule
- [ ] Budget alarms configured in billing system
- [ ] Daily review of sample responses and user feedback
Technical notes (optional)
Public-provider facts visible on the Keenable page (https://keenable.ai/):
- Index size: 100B+ documents.
- Latency: US‑East p95 reported under 250 ms.
- Pricing: public snapshot lists pricing from about $1 per 1,000 requests at 100 RPS+.
- Benchmarks: NEEDLE benchmark 7‑day mean shares of “ultimate” performance; chart bands include ~80%, 70%, 60%, 50%.
- Funding/team note: $26M raise mentioned and experienced team focused on large-index systems (https://keenable.ai/).
Acronyms: p95 = 95th‑percentile latency; RPS = requests per second; LLM = large language model; API = application programming interface.
What to do next (production checklist)
Assumptions / Hypotheses
- Assumption: Keenable provides a Console and API key workflow as shown at https://keenable.ai/.
- Hypothesis: published pricing near $1 per 1,000 requests applies at high-throughput tiers (100 RPS+); confirm your region and plan in the Console (https://keenable.ai/).
- Hypothesis: exact endpoint names, SDKs, JSON fields, and any region-specific SLAs must be confirmed in the Keenable Console before production use (https://keenable.ai/).
- Recommendation (team defaults): consider top result windows like 1–3, 3–5, or 10–20 based on query intent; treat these as implementation choices to validate in testing.
Risks / Mitigations
- Risk: unexpected cost spikes. Mitigation: add caching, budget alarms, and conservative defaults; monitor usage in Console (https://keenable.ai/).
- Risk: higher latency in non‑US regions. Mitigation: prefer US‑East for latency-sensitive flows based on the snapshot p95 <250 ms and measure region performance in tests (https://keenable.ai/).
- Risk: recall gaps for niche verticals. Mitigation: increase result window or pair with a secondary provider and validate on a representative set of queries.
Next steps
- Confirm exact API endpoints, SDK availability, quotas, and billing tiers in the Keenable Console (https://keenable.ai/).
- Implement the minimal integration and run 10–20 representative queries; record p50 and p95 latency and qualitative relevance.
- Add observability to emit latency percentiles and error rates. Set budget alerts in your billing system.
- Run a small canary and use measured metrics to adjust cache TTLs, top‑N selection, and retry/backoff parameters.
If useful, I can produce ready-to-deploy code snippets for Node, Python, or Go and a canary test matrix with gate thresholds to match your team size and SLOs.