Know where the answer came from
Chunk, label and refresh trusted content by tenant and source. Record retrieval evidence so wrong answers can be diagnosed instead of merely re-prompted.
BENGALURU / PRODUCTION AI / EVALUATED AGENTS
AI THAT IS TESTED
AS A SYSTEM.
A model can answer well and the agent can still fail. Production quality depends on retrieval, memory selection, tool contracts, tenant isolation, latency budgets, observability and a disciplined path for approved learning.
RAG + citationsRole isolationLatency routingReviewed learning
PRODUCTION AI STACK
Treat every layer as testable.
Techspa designs evaluations around the complete interaction: what the agent knew, remembered, decided, called, returned and escalated.
Route work by intent and risk
Use faster models for narrow classification and direct answers; reserve deeper retrieval or reasoning for requests where the added delay creates value.
Grow scenarios, not folklore
Convert anonymised failures, objections and edge cases into versioned tests with expected behaviors, forbidden behaviors and pass thresholds.
VERIFIED MARKET CONTEXT
Learning mode requires review and rollback.
Production feedback can propose knowledge gaps, new intents and better answers. A human reviewer approves the source or behavior change, runs regression evaluations and releases a version that can be rolled back.
The agent never silently trains on customer conversations or blends one company’s private knowledge into another tenant. Feedback becomes a candidate change, not immediate truth.
Tenant safetyKnowledge indexes, memory, tool credentials and logs are isolated by organisation.
Fast responseIntent-specific latency budgets determine retrieval depth, model route and streaming behavior.
PronunciationVoice tests include names, local terms, code-switching, interruption and low-confidence confirmation.
RegressionApproved updates must pass role, groundedness, tool, safety and conversation-history scenarios.
DELIVERY PLAN
Prove the full loop before multiplying agents.
A first role should complete its defined job from conversation through system action and measured human acceptance.
01Specify role and evaluation set
02Ingest and verify business sources
03Connect actions with permission controls
04Review production gaps and release versions
NEXT BEST PATH
Explore the relevant route.
Choose the most specific page for your requirement. This keeps the enquiry, discovery questions and recommended next step aligned with the actual commercial use case.
BUYING QUESTIONS
Answers before a sales call.
These answers describe Techspa’s current delivery approach. Final architecture, compliance and integration decisions are confirmed during discovery.
Can Techspa modernise an existing application instead of rebuilding everything?
Yes. The discovery phase identifies stable components, risky dependencies, data migration needs and the smallest safe release. Rebuilds are recommended only when extension would create greater long-term cost or operational risk.
How is personal data handled in an India deployment?
Techspa can implement consent, purpose, access, retention, correction and deletion controls. The client remains responsible for confirming the applicable DPDP obligations and any sector-specific requirements with its advisers.
Is delivery limited to Lucknow?
No. The verified India head office is in Lucknow, while discovery, engineering and support can be delivered to organisations across India using an agreed communication and ownership model.
What should we prepare for the first meeting?
Bring one target workflow, current tools, approximate volumes, user roles, examples of failure or delay, and the outcome that matters. Sensitive production data is not required for an initial scope discussion.
START WITH ONE MEASURABLE WORKFLOW
Define one agent by its finished outcome.
Bring the role, trusted sources, system action, speed target and escalation owner. Techspa will turn them into an evaluated production plan.
QUICK ANSWER
What Techspa provides in Bengaluru.
Techspa builds production AI agents for Bengaluru businesses using role isolation, approved retrieval sources, controlled memory, permissioned tools, human escalation and scenario-based evaluation. Model routing can balance response speed, answer quality and cost for each intent instead of forcing every request through one model.
Local business contextIndia’s leading technology, SaaS, startup and engineering hub
Verified India presenceLucknow head office
Service languagesEnglish and Hindi
Commercial currencyINR
Privacy contextDigital Personal Data Protection Act and Rules
Last reviewed